Convolutional Neural Networks for Radiologic Images: A Radiologist’s Guide
Tel Aviv University · Sheba Medical Center
Abstract
Deep learning has rapidly advanced in various fields within the past few years and has recently gained particular attention in the radiology community. This article provides an introduction to deep learning technology and presents the stages that are entailed in the design process of deep learning radiology research. In addition, the article details the results of a survey of the application of deep learning-specifically, the application of convolutional neural networks-to radiologic imaging that was focused on the following five major system organs: chest, breast, brain, musculoskeletal system, and abdomen and pelvis. The survey of the studies is followed by a discussion about current challenges and future…
Citation impact
- FWCI
- 42.29
- Percentile
- 100%
- References
- 178
Authors
6- SSShelly SofferCorresponding
Tel Aviv University, Sheba Medical Center
- ABAvi Ben-Cohen
Tel Aviv University, Sheba Medical Center
- OSOrit Shimon
Tel Aviv University, Sheba Medical Center
- MMMichal Marianne Amitai
Tel Aviv University, Sheba Medical Center
- HGHayit Greenspan
Tel Aviv University, Sheba Medical Center
Topics & keywords
- Medicine
- Deep learning
- Convolutional neural network
- Radiology
- Artificial intelligence
- Field (mathematics)
- Medical physics
- Abdomen